Given the emphasis of advertising & events for this community, it’s tempting to focus on technical skills.
So much social media airtime is given over to new software, coding skills or data solutions, you would think that was all that was needed for effective analytics teams. But there is so much more to developing analysts who will make an impact in your business.
I don’t know about you, but one of the perennial issues I experience when communicating analytical findings to clients, or fellow business leaders, is to help them avoid the pitfall of assuming that correlation equates to causation.
Once a relationship can be shown between some customer characteristics and the objective of interest, say likelihood to purchase, people love to rush to hypotheses as to why this makes sense – even when it is extremely unlikely and causation has not been proven.
Now there are plenty of studies showing examples of spurious correlations, like the proportion of blue-eyed customers coming into a store in Moscow and the murder rate in Los Angeles. So, an extreme example can normally be thought up to illustrate this danger. However, too few people actually understand causality and how it can be proven statistically. This is also important because of the unconscious bias that we all have to seek to simplify problems and attribute causation as soon as possible; thus it can feel like ‘swimming up stream’ to suspend judgement and seek robust evidence.
So, I’m pleased to share this guest content, by Vincent Granville, recommending a classic text to help with this very challenge:
The latest in our series of ‘top tips’, are some thoughts on getting the most out of your Database Marketing team.
By this name (or DBM), I mean the team who provide the selections for targeted direct marketing, or pre-scored leads for inbound channels.
This may involve your team also developing that targeting, normally a mixture of explainable ‘trigger event’ and filtering by propensity to respond (say from a logistic regression model), or that targeting may be provided by your analytics team.
Starting with this post, I am going to share a weekly series of ‘3 top tips’ for maximising the value of each of the different technical teams within a Customer Insight department; starting with the research team.
None of what I’m about to share is rocket science and is probably only a reminder of what you knew already. However, these updates will comprise lessons learnt, normally from getting it wrong first, and so are practical advice “from the trenches”. Given recent content has focussed on data or analytics, I will start with some advice for leaders to maximise the value of their in-house research team. (more…)
Instead, your votes have identified 7 equally likely barriers. Perhaps it really is, as Proverbs puts it, “the little foxes who spoil the vineyard”.
They say a problem shared is a problem halved, so hopefully it helps you to understand the barriers that other leaders are facing. In this post I’ll also share some initial thoughts on interventions that may help you overcome them. (more…)
The sub-title of this book is “Can you learn to be happy?” and this question is explored through a series of short chapters summarising the most popular course at Harvard today.
This might seem a strange topic for this blog, but my coaching work with customer insight leaders has taught me the power of Positive Psychology. It is also a short (168 pages) book, fun and very accessible; so a good compliment to some of the weightier tomes that I’ve reviewed here. (more…)